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Dissertation defense

  1. 1. 1 Katherine Chuang @katychuang UNDERSTANDING USER INTERACTION PATTERNS IN HEALTH SOCIAL MEDIA May 30, 2013 - Dissertation Defense College of Information Science & Technology Drexel University
  2. 2. Acknowledgements 2 —  Thesis Advisory Committee: ¡  Dr. Christopher C. Yang (chair) ¡  Dr. Jennifer Unger ¡  Dr. Jung-Ran Park ¡  Dr. Margo Orlin ¡  Dr. Weimao Ke
  3. 3. Pensieve “One simply siphons the excess thoughts from one's mind, pours them into the basin, and examines them at one's leisure. It becomes easier to spot patterns and links, you understand, when they are in this form.” — Albus Dumbledore to Harry Potter (4th book of series, Chapter 30) 3
  4. 4. Imagine you search for this… 4
  5. 5. And you click on the first result… 5 —  Hmm.. Megan has the same question as me. —  5 replies… ¡  Personal stories given ¡  Book recommendations
  6. 6. Possible Reaction to the UI 6 “I wonder if that advice would apply to me…” “Gosh, I don’t feel comfortable responding to the whole group…” —  There are different facets of communication (Farnham and Churchill, 2011)
  7. 7. A possibility… 7 A possibility to stay in contact with less exposure.
  8. 8. Social Networking Features Available 8
  9. 9. 9 Online Health Social Networking “e-patients are looking for ‘just-in-time someone- like-me’ health information” - Boase et al, 2006; Fox & Jones, 2009 *E-patient: internet user that is looking for health information “e-patients are looking for a sense of community” -Wright & Bell, 2003 41% read patient blog, health newsgroup, or health website 39% used social networking site 12% shared updates or viewed updates
  10. 10. Significance of Study 10 —  Previous research has different perspectives: ¡  Issues that concern Health Professionals ¡  Issues that concern E-Patients ¡  Issues that concern Health Records —  Expand scholarly literature ¡  Compared CMC formats within one online community. ¡  Use mixed techniques for samples. —  Fill limitations in previous work ¡  There are still gaps in understanding the technology.
  11. 11. Previous Studies This Study 11 Filling Gaps Found in Related Research
  12. 12. Theoretical Framework = Technical and Social factors Online communities are a combination of technical and social factors (Latour, 1992; Preece, 2000). Members communicate through text-based computer mediated communication (CMC) formats. Support communities are composed of people who are building relationships and exchanging social support. 12
  13. 13. Research Themes —  Observations: ¡  Some users are more active, others lurk ¡  Some are new to community ¡  Social roles (i.e. alcoholic, friend of alcoholic).. — CMC formats have different features ÷ Who can write? read? Where is the message saved? 13
  14. 14. Research Method Part 1 14 —  Reveal interaction patterns in user content —  Social media is used by health consumers to … ¡  Communicate health information ¡  Share social support ¡  Build friendships with each other —  Significance of studying e-patient interactions •  Reports show that internet use for health information is growing (Kielstra, 2009; PEW Research Ctr, 2006, 2009, 2010)
  15. 15. Medhelp.org “connects people with the leading medical experts and others who have similar experiences” “helping patients find answers to their questions” “helping patients actively manage their health” • Founded in 1994 •  Oldest online community •  Pioneer of online health communities • 10 mil monthly visitors 15
  16. 16. 16 Profile Page contains… •  Forum: Public Q&A •  Journals: Diary Style •  Notes: Profile Posts Notes Forum Journal
  17. 17. Related studies only focus on one CMC 17 Author Data Type Preece (1999) Torn Knee Ligament Email List Braithwaite et al (1999) “Support Network” Email List Bambina (2007) Support OnLine Cancer Forum Email List (stored online) Meier et al (2007) 10 cancer mailing lists Mailing lists Pfiel & Zaphiris (2007) Depression/Seniors   Bulletin Board Cunningham et al (2008) Alcoholism Bulletin Board Eichhorn (2008) Eating Disorder msg boards Yahoo Discussion Groups Coursaris & Liu (2009) HIV/Aids Bulletin Board McCormack (2010) Anorexia Bulletin Board Bulletin Board Selby et al (2010) Smoking cessation Web assisted tobacco intervention, bulletin board
  18. 18. Objective —  Understand prevalence and characteristics of different support types that peers exchange. ¡  Categories come from literature review on social support ¡  Categorize messages into support types ÷  Dimensions: ¢  Offered vs requested ¢  Post vs comments 18
  19. 19. Research Theme 1 19 Research Question •  RQ1: What social support patterns exist in messages exchanged by members of an online health community? Objective •  Study the patterns of social support exchanges of 3 CMC formats: Forums, Journals, Notes Approach •  Descriptive Content Analysis •  Coding: social support types for each message
  20. 20. Medhelp Alcoholism Community 20 Forums (n = 493) •  [FP] 81 posts •  [FC] 412 comments Journals (n = 423) •  [JP] 88 posts •  [JC] 335 comments Notes (n = 1180) 3 Months June-Sept 2009
  21. 21. Approach 1.  Data source = MedHelp.org Alcoholism 2.  Data collection = crawler 3.  Unit of analysis = each message 4.  Convert text files to Excel spreadsheets 5.  Time Frame: 1.  9th June 2009 – 9th September 2009 21
  22. 22. Informational Support Support Definition Example Advice Offers ideas and suggests actions to deal with situation (Cutrona & Suhr, 1992). “Campral works better...ask u r doc about it!” Referral Refers the recipient to some other source of help. “Im gonna send you a link that might help.” Fact reassesses the situation and presents facts. “Drinking too much alcohol daily can be a high risk to your health, you might fall into alcohol addiction.” Personal experience stories about person’s experiences. “I have been going though something like that with an addict using in our bathroom and….” Feedback / Opinion a view or judgment formed about something, not necessarily based on fact or knowledge. “From what have you posted, it seems that you are in the stage where you have been looking to drink everyday and it is a clear sign of alcohol addiction.” 22
  23. 23. Nurturant Support Support Definition Example Esteem posts providing positive comments to praise support seekers abilities or to alleviate feelings of guilt. “Congratulations on your sobriety!” Network posts providing messages to broaden support seekers social network so they don’t feel alone. “Just reach out and I will be there ok?” Emotional posts providing understanding of situation, express sorrow, provide with hope and confidence. “You're going through a rough time....” or “Hang in there hon” 23
  24. 24. 1. Text files 24
  25. 25. 2. Excel file 25
  26. 26. 3. Coding posting for self (M); friend (B); family member (F); spouse (S); sig other (SO). 0 = Offered; 1 = Request; 2 = both 26
  27. 27. What patterns of social support exchanged emerge? 27 1 –High amount of msgs offered informational support 2 –High amount of msgs offered nurturant support 3 –Low amount of msgs requested supports
  28. 28. Research Framework 28
  29. 29. People want to stay in touch 29 “Positive comments are observed between MySpace friends” -Thelwall & Wilkinson, 2010 “Friending enables users to form and maintain connections” - Ahn et al, 2007 “Private and public messaging allow for interpersonal communication” - Thellwall & WIlkinson, 2010 “SNS users expect to gratify their social-emotional needs” - Rau et al, 2008
  30. 30. Health Social Networking 30 —  Health Context… ¡  Hundreds of support communities ÷  Cancer, pregnancy, mental health, substance abuse, etc. ¡  More features than old software: ÷  Bulletin Boards (BB), email lists, discussion boards, blogs, etc. ÷  ‘Friending’ and status updates, notes
  31. 31. Research Theme 2 31 Research Question •  RQ2: What social network structure patterns emerge in messages exchanged by members of an online health community? Objective •  Study the patterns of social support exchanges of 3 CMC formats: Forums, Journals, Notes Approach •  Social Network Analysis •  Metrics: structural and positional
  32. 32. Social Graph Representations 32
  33. 33. Part 2: Social Network Analysis 33 —  Structural Metrics ¡  Centrality Measures: gives a rough indication of a person’s "connectedness" the network. ÷  In Degree: the number of people that talk to him/her ÷  Out Degree: the number of people he/she talks to ¡  Geodesic Distance = shortest distance between two specific nodes ¡  Density = number of edges / number of nodes —  Positional Metric ¡  id different roles of a group setting —  Positional analysis to Know range of roles and characteristics to make recommendations for designing a social support system that is suitable for users
  34. 34. Centrality 34 —  Betweenness = the number of people who a person is indirectly connected (i.e. controls flow of information) —  Eigenvector = influence of a node —  Closeness = based on shortest paths; measures distance to spread information from a node x to all other nodes sequentially
  35. 35. Some Insights 35 —  Forum: ¡  User reach out to a wider group of people and hold group conversations. ¡  They tend to be on receiving end. —  Journal: ¡  Tend to be writing messages and to a smaller audience —  Notes: ¡  Less overlapping connections, one to one conversations
  36. 36. Image Matrix Reduced Graph 1 2 3 4 1 0 1 0 0 2 0 0 0 1 3 0 0 0 0 4 0 0 0 0 36 Procedure c1 (n=21) c2 (n=1) c4 (n=29) c3 (n=41)
  37. 37. Social Positions 37 —  Isolates: nodes with neither indegree nor outdegree —  Transmitters: nodes with only outdegree —  Receivers: nodes with only indegree —  Carriers: nodes with both indegree and outdegree.
  38. 38. Configurations of Ties between Social Positions 38 Tie Meaning Self loop   A single cohesive subgroup and an isolated position   One tie between positions   Transmitting end is providing support Receiving end is requesting support   Self loop for each position   Two subgroups   Two ties from node: self loop and regular tie   Distinguishes between an “active” position and a “passive position”   Two ties to node: self loop and regular tie   Resembles a core-periphery system. The position of more indegrees has been around longer than the other position.  
  39. 39. Informational Nurturant c1 (n=21) c2 (n=1) c4 (n=29) c3 (n=41) c1 (n=3) c2 (n=3) c3 (n=21) c4 (n=44) 39 Forum
  40. 40. Informational Nurturant c1 (n=4) c2 (n=5) c3 (n=6) c4 (n=50) c1 (n=10) c2 (n=4) c3 (n=13) c4 (n=75) 40 Journal
  41. 41. Informational Nurturant c1 (n=14) c2 (n=1) c3 (n=2) c4 (n=23) c1 (n=17) c2 (n=1) c3 (n=2) c4 (n=32) 41 Notes
  42. 42. Summary 42
  43. 43. Selected Publications 43 —  K. Chuang and C. C. Yang, “Interaction Patterns of Nurturant Support Exchanged in Online Health Social Networking” Journal of Medical Internet Research 2012; 14(3):e54. URL: http://www.jmir.org/2012/3/e54/ —  K. Chuang and C. C. Yang, “Informational Support Exchanges on Different Computer-mediated Communication Formats in a Social Media Community of Alcoholism” Journal of American Society for Information Science & Technology (forthcoming) —  K. Chuang and C. C. Yang, “How Do E-Patients Connect Online? A Study of Social Support Roles in Health Social Networking.” Conference for Social Computing, Behavioral Modeling and Prediction (SBP 2013), Washington, DC. volume 7812. p:193-200. doi: 10.1007/978-3-642-37210-0_21
  44. 44. Contributions 44 —  Recommendations to design online intervention program ¡  Assists efforts to promote healthy behaviors ¡  Identifying these users would be useful for targeting messages to segmented groups —  Show that people still behave in a way parallel to offline world —  Multiple techniques to find new patterns in use of CMC formats ¡  Compares multiple CMC formats within an online community (rather than across communities)
  45. 45. Discussion: Participation 45 —  Participation influenced by social-psychological reasons… ¡  information needs, desire to be altruistic, stigmas ¡  Social Roles (i.e. caretaker, patient, nurse, friend, etc) —  The more time people spend in an online group, the larger their online social network and the higher the satisfaction with the received support.
  46. 46. Early Web 2.0 Social Network Sites —  Elements: ¡  Post a group message —  Shared community —  Examples: Discussion boards, Email lists, Q&A —  Elements Profile + Declare people as friends + Write Public comments —  Ego-centric community —  Examples: twitter, facebook, myspace Discussion: New Media 46
  47. 47. Discussion: Technology Design —  SNS software design emphasizes relationships —  SNS give users a sense of egocentric community —  Inherent design differences – relationship structure, communication properties —  SNS can be used for healthcare needs to stimulate relationships between users. —  Some formats such as Journal/Notes lead to greater levels of intimacy and stronger social support —  Virtual support complements real-life social relationships with fewer stigmas 47
  48. 48. Limitations 48 —  Cannot generalize alcoholism community to other health conditions. —  Content analysis technique can be made stronger ¡  i.e. use Key Phrases for content analysis to have reproducible results
  49. 49. T H A N K Y O U . C O N T A C T : @ K A T Y C H U A N G O N T W I T T E R 49 The End.

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